1 . Chegg Subject Matter Expert : Advance Physics

Description : 

• Provide expert solutions and explanations for physics questions to assist students in their learning process.

• Participate in regular training to stay updated with the latest developments in physics.

• Collaborate with other experts and engage in knowledge exchange to enhance subject matter expertise.

 2 . Radio Astronomy Instrumentation , Observations and Data Analysis

Description : 

My Research work at Raman Research Institute and Gauribidanur Radio Observatory as Visiting Student involves  Desgining and Simulation of Log Periodic Dipole Antennas and Setup at G.R.O and next implementation and testing of the antenneas at G.R.O which include hands on work on RF Electronics and doing Transit observations of Sun and Galactic Plane. Devloped a web interface for L.P.D.A Setup at G.R.O for Remote observations,Data Storing and Processing.

Skills and Techniques : 

• Antenna Designing and Simulations

• RF Electronics

• Radio Astronomy Instrumentation

• Radio Astronomy Observations

• Astronomical Data Analysis 

 2 . Pulsar Imaging Analysis using Radio Astronomy Data

Description : 

My research project focuses on pulsar imaging analysis using radio astronomy data. The project started in November 2022 and is still ongoing. Initially, I learned about various data analysis techniques such as blind search, targeted search, timing analysis, and imaging analysis, and found image analysis particularly interesting.

In this project, I have been analyzing pulsar data from the National Centre for Radio Astrophysics (NCRA) using the Common Astronomy Software Applications (CASA). Specifically, I have been using CASA to perform imaging analysis on the pulsar data, which involves reconstructing images of the sky from the data collected by the radio telescope. This has involved developing and refining my understanding of the underlying physics, mathematics, and computer programming involved in the data analysis process.

Skills and Techniques : 

Throughout this project, I have developed a range of technical skills and techniques, including :

• Proficiency in using CASA software for radio astronomy data analysis.

• Familiarity with the basics of radio astronomy, including radio telescopes, pulsars, and the radio emission from astrophysical objects.

• Experience with image analysis and reconstruction techniques.

• Familiarity with basic programming languages such as Python and Unix shell scripting.

Acknowledgments : 

I would like to acknowledge the National Centre for Radio Astrophysics (NCRA) for providing the data for this project, and my research supervisor Dr. Mayuresh Surnis  for his guidance and support throughout the project.

 3 .  Quantum Machine Learning Internship

Description : 

This research project was part of a winter internship program focused on quantum machine learning. Over the course of two months, I revisited and learned new concepts in quantum mechanics and machine learning, before proceeding to read a general paper about quantum machine learning and the HHL algorithm. As part of the program, we attended a tutorial where a person doing her MS thesis in quantum machine learning explained qubits and the IBM quantum server and how to use it.

Finally, we were able to select some papers to read and report on. For my project, I chose the paper "Quantum Algorithm for Data Fitting," which I read and then conducted further research on to write a report. At the end of the internship, we all shared our work by presenting our findings and research to the group.

Skills  : 

Throughout this project, I have developed a range of technical skills and techniques, including :

• Familiarity with quantum mechanics and qubits.

• Understanding of the HHL algorithm.

• Experience with the IBM quantum server.

• Research and analysis skills.

• Technical writing and presentation skills.

Acknowledgments : 

I would like to thank my college for providing me with this winter internship opportunity and my mentor for guiding me throughout the project. I am also grateful to the authors of the paper "Quantum Algorithm for Data Fitting" for their valuable contributions to the field of quantum machine learning.